Chinese tech employees are being asked to train AI clones of themselves for livestreaming, customer service, and content creation—and some are starting to push back against the synthetic doubles replacing them.
A technical exploration of why large language models behave as probabilistic samplers rather than deterministic functions, and why this distinction fundamentally changes how we should evaluate, deploy, and trust them.
Moonshot AI and Tsinghua researchers unveil PrfaaS, a cross-datacenter KVCache architecture that decouples prefill from decode to dramatically improve LLM serving efficiency at scale.
AWS Trainium accelerators combined with speculative decoding offer a remedy for the autoregressive bottleneck in LLM inference, dramatically reducing latency while preserving output quality through draft-and-verify token generation.
Kyutai's Unmute framework brings modular, low-latency voice capabilities to any LLM, combining streaming STT, TTS, and the Mimi neural codec for real-time conversational AI.
A technical walkthrough of deploying PrismML's Bonsai 1-bit LLM on CUDA using GGUF quantization, with benchmarking, structured JSON output, chat, and retrieval-augmented generation pipelines.
Streaming speech recognition and full-duplex conversational AI are reshaping how voice assistants work. Here's why low-latency listening matters for the next generation of speech LLMs and voice-driven synthetic media.
Sam Altman's World project partners with Zoom to bring proof-of-human verification to video meetings, tackling the rising threat of real-time deepfake impersonation in enterprise communications.
Knowledge distillation lets smaller AI models inherit capabilities from larger ones. Here's how the technique works, why it matters for synthetic media models, and why it sits at the center of today's biggest AI controversies.
Secured Signing reports 45% month-on-month growth in notary adoption of its deepfake detection feature, signaling rapid uptake of synthetic media defenses in remote online notarization workflows.
A roundup of leading AI red teaming tools used to probe, stress-test, and harden machine learning models against adversarial attacks, jailbreaks, and data leakage in 2026.
NVIDIA's Nemotron-OCR-v2 leverages large-scale synthetic data to deliver fast, multilingual document OCR, pushing the envelope on efficient vision-language models for structured text extraction.